Assessment of infection risk of Omicron variant in subways based on smartcard swipe data

Abstract

Background

Public transportation, particularly subway systems, is an essential component of many individuals' daily routines and may significantly influence the spread of infection.

Objective

This study evaluated the risk of transmission of the SARS-CoV-2 Omicron variant in subway carriages and the effectiveness of different interventions based on real travel behaviors in Beijing.

Methods

Data on nearly 58 million smartcard swipes for subway rides were collected between April 12 and 18, 2017, before the pandemic, and between February 22 and 28, 2022, during the pandemic period. These smartcard-swipe data were used to analyze changes in local travel behavior due to the COVID-19 pandemic, the risk of infection posed by the Omicron variant, and the efficacy of diverse non-pharmaceutical interventions in subway systems.

Results

Due to the pandemic, the number of passengers in close contact (interpersonal contact within 1.5 m) on the same carriage during both rush and non-rush hours decreased by 31.9% and 43.2% respectively, compared to pre-pandemic period. The R_t value (the expected number of secondary cases infected by an index case) during the weekdays was three times that of the weekend during the pandemic week. On weekdays during the pandemic, passengers faced a markedly elevated relative risk of infection when traveling during rush hours, which constituted 92.2% of the entire day. Peak-shifting travel could reduce 55.0% of infection risk during rush hour. For the Omicron variant characterized by high infectivity, virus transmission remained uncontrollable (R_t = 1.34), even when all passengers wore surgical masks. Transmission of Omicron variant could be controlled (R_t < 1) within subway systems if over 67.5% of passengers wore N95 respirators.